There have been several attempts to use radio-frequency (RF) signals to position people or assets moving within a cluttered environment such as an urban canyon or an enclosed structure such as a building. Generally speaking, these prior art attempts typically utilize fixed reference stations or beacons together with some form of receiving or responding tag on the object to be tracked. With this apparatus, a form of triangulation using RF signal strength (RSS), time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA) phenomena from the reference stations is used to determine the position of the tag.
One deficiency of most of these prior art approaches is that they are adversely affected by the RF multipath signals generated in cluttered environments. Multipath signals can result in incorrect measurements of RSS, TOA, TDOA, and AOA phenomena when the direct path between the reference beacon and the tag cannot be reliably and consistently measured. Accordingly, these approaches typically treat multipath signals as an error to be eliminated in order to provide accurate position results.
A representative first class of approaches to the positioning problem include inertial systems; inertial systems with zero velocity updates at each stop; and augmentation or updating with Doppler measurements, barometric altitude, magnetometers, or vision systems. This class of approaches sometimes requires special algorithms to identify repeated crossing points or to provide active inertial calibration, and typically requires prior knowledge of the building dimensions and layout. Some of these approaches utilize global positioning system (GPS) or cell phone navigation aids such as E911 to the extent that a signal can be faithfully received in the cluttered environment amid shadowing.
A second class of approaches employs a cooperative infrastructure using 802.11x, Bluetooth, or another RF technique, with some infrastructures specially designed for such purposes. One specific approach uses the signal strength of network element transmitters as received by several transceivers, further mapped and calibrated against the known building structure to account for effects like absorption, refraction, and reflection. Another approach uses carrier phase measurements taken by a triangulating set of specialized transmitters or receivers. In this second class, RFID technology may also be employed to locate objects over relatively small areas, but typically requires many integrating sensors to be practical over larger areas.
One issue associated with the first class of autonomous approaches is cost. While these approaches can provide good performance, they typically employ costly elements and integrate into a costly system. Furthermore, this class of approaches typically requires each person or object to carry a navigation device, which can make the overall system expensive. While such approaches are suited to applications where autonomy is important and cost is somewhat less important, their application to commercial applications can be cost prohibitive.
Approaches from the second class enjoy the advantage of having their primary cost embedded in their infrastructure. That cost is subsequently amortized across individual users, each of whom would carry a relatively low cost receiver or transponder such as a personal digital assistant equipped with 802.11x technology. However, approaches from the second class still typically suffer from sensitivity to multipath signals.
Accordingly, there is a need for improved systems and methods that can position people or assets moving within a cluttered environment such as an urban canyon or an enclosed structure such as a building without suffering adverse effects from the multipath signals generated in these environments.